Abstract
Anthropometric data is the foundation of ergonomic design for all products and environments. However, the procedures for collecting anthropometric data are tedious, complicated and costly in terms of labor, time and financial resources. It will be much cheaper if the old anthropometric data can be updated easily without lengthy measurement processes. However, most practitioners do not know how the old anthropometric data can be converted into applicable new data when updated data is unavailable. Therefore, it is important to develop methods that can easily update old data into new data with minimal error. A last, complete and large-scale anthropometric database was built in Taiwan in the late 1990s and published in 2002. In order to maximize the value of the Taiwanese anthropometric database, the statistical/mathematical estimating model developed in this study was used to analyze the available pairwise body dimension ratios (PBD ratios) and to find the constant body ratio benchmarks (CBR benchmarks) that are least affected by gender and age. This resulted in the identification of 483 unique CBR benchmarks, which were verified by calculating and processing 35,245 PBD ratios; meanwhile, quasi-CBR benchmarks that are least affected by either gender or age were also identified. Additionally, 197 estimation formulae with limited easily-measured 19 body dimensions were built using 483 CBR benchmarks. Further, this study recruited 30 participants as samplings and determined that this estimating model is more accuracy and cost-effective. To evaluate the practicability of this estimating model on separate body dimensions, the 12 finger cun-derived benchmarks (F-cun-derived benchmarks) were constructed by using this estimating model procedure and further validated by an experimental measurement. Accordingly, the statistical/mathematical estimating model, CBR benchmarks, 197 estimation formulae, and 12 F-cun-derived benchmarks make it possible to update anthropometric data quickly, accurately, and at low cost.